6 papers
BoltNet: An Ultra-Lightweight Convolutional Network for On-Device Plant Species Identification
Daniel Rossi, Guido Borghi, Roberto Vezzani
Automated plant species identification from citizen-science imagery is an established, demanding fine-grained recognition problem: large taxonomic label spaces, visually similar sp…
Fake3DGS: A Benchmark for 3D Manipulation Detection in Neural Rendering
Davide Di Nucci, Riccardo Catalini, Guido Borghi +1
Recent advances in 3D reconstruction and neural rendering,particularly 3D Gaussian Splatting, make it feasible and simple to edit 3D scenes and re-render them as highly realistic i…
SnapPose3D: Diffusion-Based Single-Frame 2D-to-3D Lifting of Human Poses
Alessandro Simoni, Riccardo Catalini, Davide Di Nucci +6
Depth ambiguity and joint uncertainty are the two main obstacles in obtaining accurate human pose predictions by 2D-to-3D lifting methods proposed in the literature. In particular,…
GazeD: Context-Aware Diffusion for Accurate 3D Gaze Estimation
Riccardo Catalini, Davide Di Nucci, Guido Borghi +5
We introduce GazeD, a new 3D gaze estimation method that jointly provides 3D gaze and human pose from a single RGB image. Leveraging the ability of diffusion models to deal with un…
BRUM: Robust 3D Vehicle Reconstruction from 360 Sparse Images
Davide Di Nucci, Matteo Tomei, Guido Borghi +3
Accurate 3D reconstruction of vehicles is vital for applications such as vehicle inspection, predictive maintenance, and urban planning. Existing methods like Neural Radiance Field…
TakuNet: an Energy-Efficient CNN for Real-Time Inference on Embedded UAV systems in Emergency Response Scenarios
Daniel Rossi, Guido Borghi, Roberto Vezzani
Designing efficient neural networks for embedded devices is a critical challenge, particularly in applications requiring real-time performance, such as aerial imaging with drones a…